Data processing systems are frequently utilized for processing large volumes of data. In order to provide this functionality, data processing systems may include multiple data storage targets to which input data is routed for storage and/or analysis. One form of data storage target is a data warehouse that aggregates data from many operational systems and/or data stores. Other data storage targets may include graphing tools configured to plot or graph the data, applications for organizing/querying the data, and other similar data targets. For example, input data for an online retailer may include data from many sources, including data relating to customer purchases, data relating to network page views, data relating to a catalog of products, data relating to search queries, and many other types of data. The online retailer may execute reports, perform various types of analyses, and perform other types of functions using the data from the data storage targets to determine, for example, various types of information related to a state of one or more portions of a retail system maintained by the online retailer.
As the data maintained by data processing systems is frequently utilized for many different types of engineering and business purposes, the quality of the data routed to and maintained by data storage targets such as those described above may be very important. Due to the typically large quantity of data maintained by the data storage targets, however, it can be difficult to ensure the quality of the data stored in these types of systems.
The disclosure made herein is presented with respect to these and other considerations.